Curt Tigges

Deep Learning Interpretability Researcher

I do LLM interpretability research and engineering at Decode Research, parent organization of Neuronpedia. My research involves a number of areas, including feature representation, sparse autoencoders (SAEs), circuit discovery, the study of world modeling, and developmental interpretability. I've also done some work with model training and fine-tuning.

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Technical Foci

Mechanistic Interpretability

Most of my research focuses on mechanistic interpretability for large language models. I find discovery of the internal patterns, features, and workings of these models quite exciting, and am also very interested in their application for AI risk reduction.

Developmental Interpretability

In addition to other topics in mechanistic interpretability, I have significant research interest in the evolution of latents/features, circuitry, and capabilities over the training process, with a focus on phase transitions and the sensitivity of models to the order of training data.

Software Engineering & MLOps

In addition to writing code in short sprints for research purposes, I strive to produce high-quality deployment-quality code following best engineering practices (as opposed to "research-style" code). I've also focused on developing a range of skills surrounding model management, training and deployment.